package com.atguigu.chapter07;

import com.atguigu.chapter05.WaterSensor;
import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.streaming.api.datastream.KeyedStream;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.datastream.WindowedStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.windowing.ProcessWindowFunction;
import org.apache.flink.streaming.api.windowing.assigners.TumblingProcessingTimeWindows;
import org.apache.flink.streaming.api.windowing.time.Time;
import org.apache.flink.streaming.api.windowing.windows.TimeWindow;
import org.apache.flink.util.Collector;

/**
 * TODO
 *
 * @author cjp
 * @version 1.0
 * @date 2021/3/6 9:12
 */
public class Flink04_WindowFunction_Process {
    public static void main(String[] args) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);

        SingleOutputStreamOperator<WaterSensor> sensorDS = env
                .socketTextStream("localhost", 9999)
                .map(new MapFunction<String, WaterSensor>() {
                    @Override
                    public WaterSensor map(String value) throws Exception {
                        // 切分
                        String[] line = value.split(",");
                        return new WaterSensor(line[0], Long.valueOf(line[1]), Integer.valueOf(line[2]));

                    }
                });

        // 分组之前开窗：所有的数据都会进入同一个并行实例
//        sensorDS.windowAll()

        KeyedStream<WaterSensor, String> sensorKS = sensorDS.keyBy(sensor -> sensor.getId());

        // 分组之后开窗：
        WindowedStream<WaterSensor, String, TimeWindow> sensorWS = sensorKS
                .window(TumblingProcessingTimeWindows.of(Time.seconds(5))); // 滚动窗口： 窗口大小



        sensorWS
                .process(new ProcessWindowFunction<WaterSensor, String, String, TimeWindow>() {
                    /**
                     * 全窗口函数： 每来一条数据，就先存起来，到了需要输出的时候，一起计算
                     * @param key   分组的key
                     * @param context   上下文
                     * @param elements  数据，窗口内（都是同一分组）的所有数据
                     * @param out   采集器
                     * @throws Exception
                     */
                    @Override
                    public void process(String key, Context context, Iterable<WaterSensor> elements, Collector<String> out) throws Exception {
                        out.collect("key=" + key + "\n" +
                                "数据条数:" + elements.spliterator().estimateSize() + "\n" +
                                "窗口是:[" + context.window().getStart() + "," + context.window().getEnd() + ")\n\n");
                    }
                })
                .print();


        env.execute();
    }
}
